The environment of a remote sensing system for hyperspectral imagery (HSI) is well described in “Hyperspectral Image Processing for Automatic Target Detection Applications” by Manolakis, D., Marden, D., and Shaw G. (Lincoln Laboratory Journal; Volume 14; 2003 pp. 79-82). An imaging sensor has pixels that record a measurement of hyperspectral energy. An HSI device will record the energy in an array of pixels that captures spatial information by the geometry of the array and captures spectral information by making measurements in each pixel of a number of contiguous hyperspectral bands. Further processing of the spatial and spectral information depends upon a specific application of the remote sensing system.
Simulating imagery such as HSI typically consists of creating a three dimensional scene populated with three dimensional models of objects, light sources and cameras and then rendering the scene from three dimensions to a two dimensional image that displays how the objects reflect light from the light sources as viewed by the cameras.
Three dimensional models are representations of three dimensional objects whereby a collection of points are defined in three dimensional space. The representation of an object is then defined as the collection of three dimensional points and a geometric model for connecting the set of three dimensional points. Typical models used to connect these three dimensional points are triangles, lines and curved surfaces. A three dimensional scene may be constructed by establishing the geometric relationship between the modeled three dimensional objects. Well-known software tools for creating three dimensional models and scenes include Rhinoceros® 3D, Blender, Pro/ENGINEER® and OpenGL®.
Not only will a three dimensional scene have a geometrically dispersed set of models of objects, it may also have a geometrically dispersed set of light sources to provide a model of illumination. These models may represent any light source with examples ranging from the sun to the headlights of an automobile. As with actual light sources, the models of sources of illumination may have specific properties at different wavelengths. An accurate model of a light source may establish the relationship between the spectral irradiance of the source and the wavelength or hyperspectral band being modeled. A common property used to characterize and model a light source is emissivity. Emissivity is the ratio of energy radiated by a source to energy radiated by a black body object at the same temperature. For example, it is well-known that the sun may be modeled as a black body radiator with a temperature of about 5,800 K.
Many three dimensional modelers may consider the intervening medium between light sources and the objects in the scene. Incorporating atmospherics into the three dimensional scene may provide a more accurate rendering of the simulated imagery for the scene. Atmospherics are used to model the transmissivity or attenuation of light as it is transmitted from a light source to an object. Like the modeling of light sources, the model may be refined as a function of hyperspectral band. For example, it is well-known that sunlight is heavily attenuated in narrow bands in the infrared spectrum due to absorption of radiation by water and carbon dioxide in the atmosphere. A well-known tool for modeling of the atmospheric propagation of electromagnetic radiation is MODTRAN®.
Objects in the three dimensional scene may be constructed of materials that are representative of their real-world counterparts. Materials define the color, transparency, shininess etc. of the modeled object.
After the scene is populated with objects and light sources an image is generated by a process commonly known as 3D rendering. 3D rendering is a computer graphics process where three dimensional models and scenes are converted into two dimensional images that represent how the objects appear at the position of a camera that has been placed in the scene.